- Update to 2.10.0
  * boo#1203507 (CVE-2022-35934)
- Breaking Changes
  * Causal attention in keras.layers.Attention and
    keras.layers.AdditiveAttention is now specified in the call()
    method via the use_causal_mask argument (rather than in the
    constructor), for consistency with other layers.
  * Some files in tensorflow/python/training have been moved to
    tensorflow/python/tracking and tensorflow/python/checkpoint.
    Please update your imports accordingly, the old files will be
    removed in Release 2.11.
  * tf.keras.optimizers.experimental.Optimizer will graduate in
    Release 2.11, which means tf.keras.optimizers.Optimizer will
    be an alias of tf.keras.optimizers.experimental.Optimizer. The
    current tf.keras.optimizers.Optimizer will continue to be
    supported as tf.keras.optimizers.legacy.Optimizer,
    e.g.,tf.keras.optimizers.legacy.Adam. Most users won't be
    affected by this change, but please check the API doc if any
    API used in your workflow is changed or deprecated, and make
    adaptions. If you decide to keep using the old optimizer,
    please explicitly change your optimizer to
    tf.keras.optimizers.legacy.Optimizer.
  * RNG behavior change for tf.keras.initializers. Keras
    initializers will now use stateless random ops to generate
    random numbers.
    - Both seeded and unseeded initializers will always generate
      the same values every time they are called (for a given
      variable shape). For unseeded initializers (seed=None), a
      random seed will be created and assigned at initializer
      creation (different initializer instances get different (forwarded request 1005091 from bnavigator)

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